Abstract

This paper explores how ideas from actor-network theory (ANT) can be drawn on to inform ways of using computer assisted qualitative data analysis software (CAQDAS) in an ANT-oriented project. Through this it explores some of the challenges ANT poses to conventional uses of such tools, and the resources ANT provides for re-considering their agency in research practices and possibilities for future developments.

CAQDAS is often associated with particular approaches to engaging with data (e.g. coding data and retrieving the codes, abstracting and reducing data to themes etc.). These approaches have become dominant enough such that they are often presented and/or interpreted as the right, or only way to work qualitatively with qualitative data. In opposition to this orthodoxy some orienting principles are proposed from the ANT literature along with its intellectual antecedent ethnomethodology.

The proposed principles are: freedom of movement and data, logging the enquiry using Latour’s four notebooks, coding and following heterogeneous actants as cases, supporting contextual exploration of fluid and multiple ontologies, staying close to the words of the actants and working in a scale-free manner that enables shifting magnifications and assemblages to preserve detail rather than abstract it into themes. A final principle concerns the intentions of ANT-informed approaches to assemble a detailed description, which are contrasted with the intentions of approaches aligned with Grounded Theory to abstract data I order to construct an explanation.

These principles are explored and illustrated with detailed descriptions that draw on examples from a multi-modal ethnographic PhD research project. The project used heterogeneous data to explore the information infrastructures and classification systems used in craft beer judging. Examples of how that diverse dataset was coded and connected are used along with excerpts from a reflective journal of the struggles and ideas for using CAQDAS to illustrate ways of effectively using ATLAS.ti in ANT-oriented research projects.

Pecha Kucha

Using ATLAS.ti for Conversation Analysis, Discursive Psychology and other Ethnomethodological Approaches

This Pecha Kucha explores distinct and powerful features ATLAS.ti includes to support approaches to working with data for conversation analysis/discursive psychology or ethnomethodology.

Abstract

Conversation Analysis (CA) and related approaches including discursive psychology, membership category analysis (MCA) and ethnomethodology (EM) are marked by distinct methods, approaches and conventions which differ from many other approaches to working with qualitative data. Highly detailed conventions for transcription and a focus on the sequential or categorical work to achieve and display understanding in turns-at-talk and action are hallmarks of these approaches, along with the extensive use of both audio and video resources. Despite assertions that “it is unusual for conversation analysts to use CAQDAS packages because the micro-examination of patterns of talk they are concerned with often involve very small datasets” (Lewins and Silver, 2014) this Pecha Kucha considers several distinct and powerful features ATLAS.ti has to support EM/CA/MCA work including: sequencing transcripts to multiple media files, visualising the audio through waveforms, enabling multiple synchronisation points per line of text (unlike many other QDA packages), the possibilities of using contextual operators in queries to look for patterns of turns-before or turns-following, and the opportunities for hyperlinking between quotations to display principles such as next-turn proof procedures.Even with small datasets these powerful features can support close work with the text and powerful queries, as well enabling connecting and synthesising detailed CA work to broader ethnographic approaches.

Conference presentation

Presentation Slides (PDF)This work-in-progress paper explores how QDA software is used in the practices of qualitative research drawing on actor-network theory (ANT) and what ANT’s ideas can offer to understanding QDA software.